Cable Number Detection and Recognition Based on MSER and CNN

In order to solve the problem of automation of cable number identification in the process of cable assembly of large equipment, we proposed a cable number detection and recognition method based on image Maximally Stable Extremal Regions (MSER) and convolutional neural network (CNN). We used image processing algorithms combined with deep learning to achieve end-to-end identification of cable number images. In view of the uncertain arrangement order and scattered distribution of numbers on the cable, the MSER algorithm was improved by image processing in order to extract the area containing numbers more accurately. The number identification problem in the case of lack of sample database is solved by the migration-trained CNN network. In addition, the recognition effect of the method under different environmental conditions has been studied. Through experimental research, the optimized MSER and CNN algorithms can better complete the cable number detection and identification tasks.